User identity verification method, apparatus and system

ABSTRACT

This specification discloses a user identity verification method, apparatus, and system, relating to the field of information technology. The method comprises: receiving a facial image and one or more eye-print pair images corresponding to an identity verification object from a client, wherein a number of the one or more eye-print pair images corresponds to a number of eye-print collection steps, comparing the facial image to a preset facial image and comparing the one or more eye-print pair images to preset eye-print templates, and sending successful identity verification information to a client when comparison results for the facial image and the one or more eye-print pair images meet preset conditions.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 16/282,102 filed on Feb. 21, 2019, which is acontinuation application of International Application No.PCT/CN2017/096987, filed on Aug. 11, 2017, which claims the benefit ofthe Chinese Patent Application No. 201610717080.1 filed with the StateIntellectual Property Office (SIPO) of the People's Republic China onAug. 24, 2016. The entire contents of the above-identified applicationsare incorporated by reference herein.

TECHNICAL FIELD

This invention relates generally to the field of information technology,and more particularly some embodiments relate to a user identityverification method, apparatus, and system.

BACKGROUND

With the continuous development of information technologies and theInternet, a variety of applications have emerged. Of these, more andmore financial institutions are providing users with apps to manageassociated financial transactions. To ensure the security of userinformation, it is necessary to perform identity verification of theusers managing financial transactions through apps, that is, performinguser security verification operations such as identity authenticationand name authentication.

Today, user identity verification is normally performed by employing amethod of combining facial image recognition with live facial imageverification, i.e. issuing facial movement parameters to the user whenverifying a collected facial image, and requiring the user to completelive movement verification according to these movements. However, now itis possible to synthesize lifelike 3D facial images and simulate userfacial movements and expressions, resulting in low precision andreliability for existing user identity verification methods, and makingit unlikely to ensure the security of the apps used by users.

SUMMARY

In view of this, the disclosed embodiments of this specification providea user identity verification method, apparatus, and system that solvethe problems of low precision and reliability in the user identityverification methods of current technologies.

In one aspect, an embodiment of this specification provides a useridentity verification method, comprising:

receiving a facial image and one or more eye-print pair imagescorresponding to an identity verification object from a client, whereinthe number of the one or more eye-print pair images corresponds to anumber of eye-print collection steps;

comparing the facial image to a preset facial image, and comparing theone or more eye-print pair images to preset eye-print templatescorresponding to the identity verification object;

when comparison results for the facial image and the one or moreeye-print pair images meet preset conditions, sending successfulidentity verification information to the client.

In another aspect, an embodiment of this specification provides anotheruser identity verification method, comprising:

collecting a facial image and one or more eye-print pair imagescorresponding to an identity verification object, the number of the oneor more eye-print pair images corresponding to a number of eye-printcollection steps;

sending the facial image and the one or more eye-print pair images tothe server, causing the server to perform identity verification of theidentity verification object.

In another aspect, an embodiment of this specification provides aserver, comprising:

a receiving unit, configured to receive a facial image and one or moreeye-print pair images corresponding to an identity verification objectfrom a client, wherein a number of the one or more eye-print pair imagescorresponds to a number of eye-print collection steps;

a comparison unit, configured to compare the facial image to a presetfacial image, and compare the one or more eye-print pair images topreset eye-print templates:

a sending unit, when comparison results for the facial image and the oneor more eye-print pair images meet preset conditions, configured to sendsuccessful identity verification information to the client.

In another aspect, an embodiment of this specification provides aclient, comprising:

a collection unit, configured to collect a facial image and one or moreeye-print pair images corresponding to an identity verification object,the number of the one or more eye-print pair images corresponding to anumber of eye-print collection steps; a sending unit, configured to sendthe facial image and the one or more eye-print pair images to theserver, causing the server to perform identity verification of theidentity verification object.

In another aspect, an embodiment of this specification provides a useridentity verification system, comprising:

a server, when receiving a user identity verification request,configured to send, to a client, a facial quality score threshold andthe number of eye-print collection steps corresponding to the currentmode;

a client, configured to obtain a facial image based on the facialquality score threshold and obtain one or more eye-print pair images,wherein the number of the one or more eye-print pair images correspondsto the number of eye-print collections steps;

the server is also configured to receive a facial image sent by a clientand one or more eye-print pair images, wherein the number of the one ormore eye-print pair images corresponds to the number of eye-printcollection steps; compare the facial image to a preset facial image, andcompare the one or more eye-print pair images to preset eye-printtemplates; and send successful identity verification information to theclient when the comparison results for the facial image and the one ormore eye-print pair images meet preset conditions.

In another aspect, an embodiment of this specification provides anon-transitory computer-readable storage medium for user identityverification. The non-transitory computer-readable storage medium storesinstructions executable by one or more processors causing the one ormore processors to perform operations comprising:

receiving a facial image and one or more eye-print pair imagescorresponding to an identity verification object from a client, whereina number of the one or more eye-print pair images corresponds to anumber of eye-print collection steps;

comparing the facial image to a preset facial image, and comparing theone or more eye-print pair images to preset eye-print templates; and

when comparison results for the facial image and the one or moreeye-print pair images meet preset conditions, sending successfulidentity verification information to the client.

The technical solutions provided by the embodiments of thisspecification possess at least the following advantages:

The user identity verification method, apparatus, and system provided bythe embodiments of this specification comprise first receiving a facialimage and one or more eye-print pair images corresponding to an identityverification object from a client, wherein the number of the one or moreeye-print pair images corresponds to the number of eye-print collectionsteps, when a user identity verification request is received; thencomparing the facial image to a preset facial image, comparing theeye-print pair images to preset eye-print templates; and sendingsuccessful identity verification information to the client when thecomparison results for the facial image and the eye-print pair imagesmeet preset conditions. Compared to the method of combining facial imagerecognition with live facial image verification, commonly used todaywhen performing user identity verification, the embodiments of thisspecification use multidimensional verification modes such as facialverification combined with eye-print image verification and liveeye-print image verification to perform user identity verification,thereby boosting the precision and reliability of the user identityverification method, and ensuring the security of apps used by the user.

The preceding explanation is merely a summary of the technical solutionsof his invention. To enable a clearer understanding of the technicalmeasures of this invention, to enable implementation in accordance withthe content of this description, and to make the preceding and otherobjectives, features, and advantages of this invention clearer and moreeasily understood, specific implementation manners of this invention arepresented below.

BRIEF DESCRIPTION OF THE DRAWINGS

By reading the following detailed description of preferredimplementation manners, a variety of other advantages and benefits willbecome clear to persons having ordinary skill in the art. The drawingsare merely illustrative, and are not to be taken as limiting. Similarreference symbols used in all drawings represent the same components. Inthe drawings:

FIG. 1 presents a flow diagram of a user identity verification methodprovided by an embodiment of this specification;

FIG. 2 presents a flow diagram of another user identity verificationmethod provided by an embodiment of this specification;

FIG. 3 presents a flow diagram of another user identity verificationmethod provided by an embodiment of this specification;

FIG. 4 presents a flow diagram of another user identity verificationmethod provided by an embodiment of this specification;

FIG. 5 presents a schematic diagram of a server provided by anembodiment of this specification;

FIG. 6 presents a schematic diagram of another server provided by anembodiment of this specification;

FIG. 7 presents a schematic diagram of a client provided by anembodiment of this specification;

FIG. 8 presents a schematic diagram of another client provided by anembodiment of this specification;

FIG. 9 presents a diagram of a user identity verification systemprovided by an embodiment of this specification;

FIG. 10 presents a flow diagram of a user identity verification scenariopresented by an embodiment of this specification.

DETAILED DESCRIPTION

Referring to the drawings, a more detailed description of the exemplaryembodiments of this specification is given below. Even though thedrawings present exemplary embodiments of this specification, it shouldbe understood that this specification may be achieved in other forms andshould not be limited by the embodiments described here. Rather, theseembodiments are provided to enable a more thorough understanding of thisspecification and to transmit the scope of this specification in itsentirety to persons skilled in the art.

An embodiment of this invention provides a user identity verificationmethod, as shown in FIG. 1.

Referring to FIG. 1, the method includes receiving a facial image andone or more eye-print pair images corresponding to an identityverification object from a client, at 101. The number of the one or moreeye-print pair images corresponds to a number of eye-print collectionsteps.

Because a larger number of eye-print collection steps results in alonger period of time in eye-print collection, when the number of theeye-print templates of the identity verification object is ample, asmaller number of eye-print collection steps may be used; when thenumber of the eye-print templates of the identity verification object issmaller, to collect eye-print pair images for the accumulation ofeye-print templates for the identity verification object, a largernumber of eye-print collection steps may be used. In some embodiments,it is possible to further boost the precision of user identityverification by configuring different numbers of eye-print collectionsteps based on different circumstances. The server can use communicationmeans such as mobile cellular networks and WIFI networks to perform datatransmission with the client. No limitations are placed on this by theembodiments of this specification.

Referring again to FIG. 1, the method includes comparing the facialimage to a preset facial image, and comparing the eye-print pair imagesto preset eye-print templates corresponding to the identity verificationobject, at 102.

The preset facial image may be a photograph of the user that has beenregistered with a public security network, a facial photograph that hasbeen verified by a user identity verification, or the like. Nolimitations are placed on this by the embodiments of this specification.The preset eye-print templates may be multiple sets of eye-print pairimages that have been verified by a security verification process. Thecomparison operation may determine whether the degree of matchingbetween images meets preset requirements. No limitations are placed onthis by the embodiments of this specification.

Referring again to FIG. 1, the method includes sending successfulidentity verification information to the client when the comparisonresults for the facial image and the eye-print pair images meet presetconditions, at 103.

The preset conditions may include facial comparison score thresholds,eye-print match score thresholds, and the like. No limitations areplaced on this by the embodiments of this specification. In someembodiments, when both the facial image and eye-print pair imagecomparison results meet preset conditions, a successful identityverification is determined. Thus the user identity verification isperformed through multiple dimensions such as facial images andeye-print pair images, thereby boosting the precision of the useridentity verification method.

An embodiment of this specification provides a user identityverification method. When a user identity verification request isreceived, first, a facial image and one or more eye-print pair imagescorresponding to an identity verification object are received from aclient. The number of the one or more eye-print pair images correspondsto the number of eye-print collection steps. Then, the facial image iscompared to a preset facial image, and the eye-print pair images arecompared to preset eye-print templates. Successful identity verificationinformation is sent to the client if the comparison results for thefacial image and the eye-print pair images meet preset conditions.Compared to the method of combining facial image recognition with livefacial image verification commonly used today when performing useridentity verification, the embodiments of this specification usemultidimensional verification modes such as facial image verificationcombined with eye-print image verification and live eye-print imageverification to perform user identity verification, thereby boosting theprecision and reliability of the user identity verification method, andensuring the security of apps when used by the user.

Furthermore, an embodiment of this specification provides another useridentity verification method, as shown in FIG. 2.

Referring to FIG. 2, the method includes obtaining a number of preseteye-print templates corresponding to the identity verification objectfrom a preset storage location, when a user identity verificationrequest is received, at 201.

The eye-print templates corresponding to different identity verificationobjects are stored in the preset storage location. When a user needs toperform security verification such as login identity validation orpayment identity validation, a user identity verification request issent to a client.

Following step 201, the embodiments of this specification may alsocomprise when the number of eye-print templates corresponding to theidentity verification object is less than a preset threshold,determining the current mode as an eye-print enrollment mode; sending afacial quality score threshold and the number of eye-print collectionsteps corresponding to the eye-print enrollment mode to the client, tomake the client obtain a facial image based on the facial quality scorethreshold and obtain one or more eye-print pair images corresponding tothe number of eye-print collection steps; and storing the eye-print pairimages in the preset storage location as the eye-print templatescorresponding to the preset identity verification object.

It should be noted that when the number of eye-print templates is lessthan the preset threshold, it means that the number of eye-printtemplates at that time is rather low, and it may not be possible toensure the precision of an eye-print verification. At that time, thecurrent mode is determined as eye-print enrollment mode. This can enablethe client to input in real time eligible eye-prints as the eye-printtemplates of the identity verification object, thus achieving theaccumulation of eye-print templates. When the number of eye-printtemplates reaches the preset threshold, the identity verification modeis switched on, thus further boosting the precision and reliability ofthe user identity verification.

Referring again to FIG. 2, the method includes determining the currentmode as identity verification mode if the number of eye-print templatesis greater than or equal to a preset threshold, at 202.

Here, the current mode may comprise eye-print collection mode, identityverification mode, etc. The current mode is associated with the numberof eye-print templates corresponding to the user that are stored in thepreset storage location. No limitations are placed on this by theembodiments of this specification. It should be noted that for eye-printcollection mode, the collected facial eye-print image qualityrequirements are quite high, to facilitate the server's accumulation ofeye-print templates; for identity verification modes, average facialeye-print image quality is sufficient, because the server can performeye-print comparisons using previously accumulated eye-print templates.For the facial quality score threshold used to indicate the quality ofthe facial image collected by the client, a higher facial quality scorethreshold requires a higher quality in the facial image collected by theclient. The number of eye-print collection steps is used to indicate thenumber of eye-print pairs collected at one time by the client. Forexample, when the number of eye-print collection steps is 5, the clientneeds to collect 5 pairs of eye-prints.

It should be noted that, because a larger number of eye-print collectionsteps results in a longer period of time in eye-print collection, therewill be different numbers of eye-print collection steps configured fordifferent modes. For example, for identity verification mode, becausethere are an ample number of eye-print templates under this mode, asmaller number of eye-print collection steps may be configured; foreye-print enrollment mode, because this mode collects eye-print pairimages for the accumulation of eye-print templates, a larger number ofeye-print collection steps may be configured. In some embodiments, it ispossible to further boost the precision of user identity verification byconfiguring different numbers of eye-print collection steps based ondifferent modes.

Referring again to FIG. 2, the method includes sending a facial qualityscore threshold and the number of eye-print collection stepscorresponding to the identity verification mode to a client, at 203.

As such, the client can obtain a facial image based on the facialquality score threshold and obtain one or more eye-print pair imagescorresponding to the number of eye-print collection steps. Here, theclient may be configured on a mobile device with a webcam andmicrophone. These mobile devices include but are not limited tosmartphones and tablet PCs. The client can use the webcam to collectrelevant images.

Referring again to FIG. 2, the method includes receiving a facial imageand one or more eye-print pair images corresponding to an identityverification object from a client. In some embodiments, the number ofthe one or more eye-print pair images corresponds to the number ofeye-print collection steps, at 204.

The server can use communication means such as mobile cellular networksand WIFI networks to perform data transmission. No limitations areplaced on this by the embodiments of this specification.

Referring again to FIG. 2, the method includes comparing the facialimage to a preset facial image, and comparing the eye-print pair imagesto preset eye-print templates, at 205.

The preset facial image may be a photograph of the user that has beenregistered with a public security network or a facial photograph thathas been verified by a user identity verification. No limitations areplaced on this by the embodiments of this specification. The preseteye-print templates may be multiple sets of eye-print pair images thathave been verified by a security verification process.

In some embodiments, if the current mode is determined as the identityverification mode, comparing the facial image to a preset facial imagemay comprise using the facial image and the preset facial image as inputto a preset facial algorithm, and obtaining a facial comparison scorecorresponding to the identity verification object from the preset facialalgorithm. Comparing the eye-print pair images to preset eye-printtemplates comprises using the eye-print pair images and the eye-printtemplates corresponding to the identity verification object as input toa preset eye-print algorithm, and obtaining multiple eye-print livenessscores corresponding to the number of eye-print collection steps and aneye-print match score from the preset eye-print algorithm.

The preset facial algorithm and the preset eye-print algorithm may beconvolutional neural network algorithms, multi-layer neural networkalgorithms, etc. No limitations are placed on this by the embodiments ofthis specification. The facial comparison score is used to reflect thedegree to which the facial image of the identity verification objectmatches the preset facial image. A higher facial comparison score meansa higher match between the facial image of the identity verificationobject and the preset facial image. The eye-print liveness score is usedto reflect the fidelity of the collected eye-print pair images of theidentity verification object. A higher eye-print liveness score meanshigher fidelity of the eye-print pair image. The eye-print match scoreis used to reflect the degree to which the eye-print pair images of theidentity verification object match the preset eye-print templates. Ahigher eye-print match score means a higher match between the eye-printpair images of the identity verification object and the preset eye-printtemplates.

Referring again to FIG. 2, the method includes sending successfulidentity verification information to the client when the comparisonresults for the facial image and the eye-print pair images meet presetconditions, at 206.

In some embodiments, step 206 may comprise sending successful identityverification information to the client if the facial comparison score,the multiple eye-print liveness scores, and the eye-print match scoreare greater than respective preset threshold scores. In someembodiments, when the facial comparison score, the multiple eye-printliveness scores, and eye-print match score all are greater than therespective preset threshold scores, identity verification is determinedas successful, thus boosting the precision and reliability of the useridentity verification method.

Referring again to FIG. 2, the method includes, when the comparisonresults for the facial image in the one or more eye-print pair meet thepreset conditions, updating the eye-print templates corresponding to theidentity verification object that are stored in the preset storagelocation based on the eye-print pair images collected by the client, at207.

In some embodiments, when user identity verification is determined assuccessful, the eye-print pair images collected by the client at thistime are deemed true and reliable, and the eye-print templatescorresponding to the identity verification object stored in the presetstorage location are updated based on the eye-print pair imagescollected by the client. This can further ensure the accuracy of theeye-print templates corresponding to the identity verification objectthat are stored in the preset storage location, thereby further boostingthe precision of the user identity verification method.

FIG. 10 illustrates a specific application scenario flow according tosome embodiments of the present disclosure. Referring to FIG. 10, theserver may use a configured decision module, FEArbitrator, to obtain aneye-print template number of 10, corresponding to the identityverification object, at 1002. This is greater than the preset templatenumber threshold of 9, at 1004, so the current mode is determined asidentity verification mode “Verify”, at 1010. Next, a facial qualityscore threshold QT and the number of eye-print collection steps 1corresponding to the identity verification mode “Verify” is sent to theclient, at 1012. At this time, the client collects a facial image andone eye-print pairs, at 1014. Then, after determining that the qualityof the collected facial image is greater than or equal to QT,preprocessing such as optimization and compression is performed on thecollected facial image and eye-print pair image, and then thepreprocessed facial image and eye-print pair image are sent to theserver, 1016. At this time, the server uses a preset facial algorithm tocompare the facial image to a verified preset facial image and obtains afacial image comparison score FX, and uses a preset eye-print algorithmto compare the collected eye-print pair to preset eye-print templatesand obtain an eye-print liveness score LK and eye-print match score MX,at 1018. If FX is greater than or equal to the preset facial comparisonscore threshold FT, LK is greater than or equal to the preset eye-printliveness score threshold LT, and MX is greater than or equal to thepreset eye-print match score threshold, then successful identityverification information is sent to the client, at 1020 and the preseteye-print templates are updated based on the collected eye-print pairimage, at 1022. If the number of eye-print templates corresponding tothe identity verification object is less than 9, at 1004, the client isinstructed to conduct eye-print pair image collection until the numberof eye-print templates corresponding to the identity verification objectis greater than or equal to 9, and the mode is switched to identityverification mode, at 1006 and 1008.

In another user identity verification method provided by thisspecification, when a user identity verification request is received,first a facial image and one or more eye-print pair images correspondingto an identity verification object are received from a client. Thenumber of the one or more eye-print pair images corresponds to thenumber of eye-print collection steps. Then, the facial image is comparedto a preset facial image, and the eye-print pair images are compared topreset eye-print templates. If the comparison results for the facialimage and the eye-print pair images meet preset conditions, successfulidentity verification information will be sent to the client. Comparedto the method of combining facial image recognition with live facialimage verification commonly used today when performing user identityverification, this embodiment uses multidimensional verification modessuch as facial verification combined with eye-print image verificationand live eye-print image verification to perform user identityverification, thereby boosting the precision and reliability of the useridentity verification method, and ensuring the security of apps used bythe user.

Furthermore, an embodiment of this specification provides a useridentity verification method, as shown in FIG. 3. Referring to FIG. 3,the method includes collecting a facial image and one or more eye-printpair images corresponding to an identity verification object, the numberof the one or more eye-print pair images corresponding to the number ofeye-print collection steps, at 301.

Here, the executing entity of this invention embodiment may be a client.The client may be configured on a mobile device with a webcam andmicrophone. These mobile devices include but are not limited tosmartphones and tablet PCs. When the client receives a user request suchas account login or payment, a facial image and one or more eye-printpair images corresponding to an identity verification object arecollected for a server to perform security verification such as identityvalidation or payment identity validation for the user. The number ofthe one or more eye-print pair images corresponds to the number ofeye-print collection steps.

Referring again to FIG. 3, the method includes sending the facial imageand the eye-print pair images to the server, at 302.

As such, the server can perform identity verification of the identityverification object.

In some embodiments, before step 302, the method may also comprise theclient performing preprocessing of the collected facial image andeye-print pair image. The preprocessing may comprise image optimization,image segmentation, image compression, facial image quality calculation,and eye-print liveness calculation. No limitations are placed on this bythe embodiments of this specification. By performing preprocessing ofthe collected facial image and eye-print pair image, it is possible toensure the true accuracy of the image used by the server for identityverification, thereby ensuring the precision of user identityverification.

An embodiment of this specification provides another user identityverification method. First, a facial image corresponding to the identityverification object and one or more eye-print pair images correspondingto the number of eye-print collection steps are collected, then thefacial image and the eye-print pair images are sent to the server,causing the server to perform identity verification of the identityverification object. Compared to the method of combining facial imagerecognition with live facial image verification, commonly used todaywhen performing user identity verification, this embodiment usesmultidimensional verification modes such as facial verification combinedwith eye-print image verification and live eye-print image verificationto perform user identity verification, thereby boosting the precisionand reliability of the user identity verification method, and ensuringthe security of apps used by the user.

An embodiment of this specification provides another user identityverification method, as shown in FIG. 4.

Referring to FIG. 4, the method includes sending a user identityverification request to a server, at 401.

The executing entity of this invention embodiment may be a client. Theclient may be configured on a mobile device with a webcam andmicrophone. These mobile devices include but are not limited tosmartphones and tablet PCs. When the user requests the performance of anoperation such as account login or payment, a user identity verificationrequest is sent to a server, causing the server to perform securityverification of the user, such as identity validation and paymentidentity validation. The user identity verification request may includeidentification information of the user, to enable the server to extractinformation such as the user's preset facial image or preset eye-printtemplate, etc. from a database to perform subsequent user identityverification.

Referring again to FIG. 4, the method includes receiving a facialquality score threshold and the number of eye-print collection stepscorresponding to the current mode and sent by the server, at 402.

The client can use communication means such as mobile cellular networksand WIFI networks to perform data transmission with the server. Nolimitations are placed on this by the embodiments of this specification.The relevant portions of step 101 may be referenced for an explanationof the identity verification mode, facial quality score threshold, andthe number of eye-print collection steps. Further details will not berepeated here.

Referring again to FIG. 4, the method may include obtaining a facialimage based on the facial quality score threshold and obtaining one ormore eye-print pair images corresponding to the number of eye-printcollections steps, at 403.

For example, a client may use a preset webcam to obtain a facial imageand eye-print pair images of the current identity verification object.No limitations are placed on this by the embodiments of thisspecification.

Referring again to FIG. 4, the method may include determining whetherthe image quality of the currently obtained facial image is greater thanor equal to the facial quality score threshold, and determining whetherthe eye-print pair images meets preset eye-print liveness conditions, at404.

The preset eye-print liveness conditions are used to reflect theauthenticity of the eye-print pair image. In some embodiments, beforesending the facial image and the eye-print pair images to the server, bydetermining whether the image quality of the currently obtained facialimage is greater than or equal to the facial quality score threshold,and by determining whether the eye-print pair images meets preseteye-print liveness conditions, it is possible to ensure the trueaccuracy of the image sent to the server for identity verification,thereby ensuring the precision of user identity verification.

Referring again to FIG. 4, the method may include sending the facialimage and the eye-print pair images to the server if the image qualityof the currently obtained facial image is greater than or equal to thefacial quality score threshold and the eye-print pair images meetspreset eye-print liveness conditions, at 405.

As such, the server can perform identity verification of the user. Insome embodiments, after determining that the quality of the collectedfacial image and eye-print pair images meet requirements, these imagesare sent to the server. Thus it is possible to ensure the true accuracyof the images sent to the server for identity verification, therebyensuring the precision of user identity verification.

An embodiment of this specification provides another user identityverification method. First, a facial image and one or more eye-printpair images corresponding to an identity verification object arecollected, then the facial image and the eye-print pair images are sentto the server, causing the server to perform identity verification ofthe identity verification object. The number of the one or moreeye-print pair images corresponds to the number of eye-print collectionsteps. Compared to the method of combining facial image recognition withlive facial image verification, commonly used today when performing useridentity verification, this embodiment uses multidimensionalverification modes such as facial verification combined with eye-printimage verification and live eye-print image verification to perform useridentity verification, thereby boosting the precision and reliability ofthe user identity verification method, and ensuring the security of appsused by the user.

As an implementation of the method shown in FIG. 1, an embodiment ofthis specification provides a server, as shown in FIG. 5. The server maycomprise a receiving unit 51, comparison unit 52, and sending unit 53.

The receiving unit 51 is configured to receive a facial image and one ormore eye-print pair images corresponding to an identity verificationobject from a client. The number of the one or more eye-print pairimages corresponds to the number of eye-print collection steps.

The comparison unit 52 is configured to compare the facial image to apreset facial image, and compare the eye-print pair images to preseteye-print templates.

The sending unit 53 is configured to send successful identityverification information to the client if the comparison results for thefacial image and the eye-print pair images meet preset conditions.

It should be noted that this apparatus embodiment corresponds to theaforementioned method embodiment. For ease of reading, this apparatusembodiment will not go over each detail given in the aforementionedmethod embodiment, but it should be clear that the apparatus of thisembodiment is capable of achieving everything achieved in theaforementioned method embodiment.

An embodiment of this specification provides a server. When a useridentity verification request is received, first, a facial image and oneor more eye-print pair images corresponding to an identity verificationobject are received from a client. The number of the one or moreeye-print pair images corresponds to the number of eye-print collectionsteps. Then the facial image is compared to a preset facial image, andthe eye-print pair images are compared to preset eye-print templates.Successful identity verification information is sent to the client ifthe comparison results for the facial image and the eye-print pairimages meet preset conditions. Compared to the method of combiningfacial image recognition with live facial image verification, commonlyused today when performing user identity verification, this embodimentuses multidimensional verification modes such as facial verificationcombined with eye-print image verification and live eye-print imageverification to perform user identity verification, thereby boosting theprecision and reliability of the user identity verification method andensuring security when a user uses an application.

As an implementation of the method shown in FIG. 2, an embodiment ofthis specification provides another server, as shown in FIG. 6. Theserver may comprise a receiving unit 61, comparison unit 62, sendingunit 63, acquisition unit 64, determination unit 65, storing unit 66,and updating unit 67.

The receiving unit 61 is configured to receive a facial image and one ormore eye-print pair images corresponding to an identity verificationobject from a client. The number of the one or more eye-print pairimages corresponds to the number of eye-print collection steps.

The comparison unit 62 is configured to compare the facial image to apreset facial image, and compare the eye-print pair images to preseteye-print templates.

The sending unit 63 is configured to send successful identityverification information to the client if the comparison results for thefacial image and the eye-print pair images meet preset conditions.

The acquisition unit 64, when receiving a user identity verificationrequest, is configured to obtain the number of eye-print templatescorresponding to the identity verification object from a preset storagelocation, where the eye-print templates corresponding to differentidentity verification objects are stored.

The determination unit 65, is configured to determine that the currentmode is identity verification mode if the number of eye-print templatesis greater than or equal to a preset threshold.

The sending unit 63 is also configured to send a facial quality scorethreshold and the number of eye-print collection steps corresponding toidentity verification mode to a client, causing the client to obtain afacial image based on the facial quality score threshold and obtain oneor more eye-print pair images corresponding to the number of eye-printcollection steps.

The determination unit 65 is also configured to determine that thecurrent mode is an eye-print enrollment mode if the number of eye-printtemplates is less than the preset threshold.

The sending unit 63 is also configured to send a facial quality scoreand the number of eye-print collection steps corresponding to theeye-print enrollment mode to the client, causing the client to obtain afacial image based on the facial quality score threshold and obtain oneor more eye-print pair images corresponding to the number of eye-printcollection steps.

The storing unit 66 is configured to store the eye-print pair images inthe preset storage location as the eye-print templates corresponding tothe preset identity verification object.

The comparison unit 62 is configured to use the facial image and thepreset facial image as input to a preset facial algorithm, and obtain afacial comparison score corresponding to the identity verificationobject.

The eye-print pair images and the eye-print templates corresponding tothe identity verification object are used as input to an eye-printalgorithm to obtain multiple eye-print liveness scores corresponding tothe number of eye-print collection steps and an eye-print match score.

Further, the sending unit 63 is configured to send successful identityverification information to the client if the facial comparison score,the multiple eye-print liveness scores, and the eye-print match scoreare greater than respective preset threshold scores.

The updating unit 67, when user identity verification is determined assuccessful, based on the eye-print pair images collected by the client,is configured to update the eye-print templates corresponding to theidentity verification object stored in the preset storage location.

It should be noted that this apparatus embodiment corresponds to theaforementioned method embodiment. For ease of reading, for thisapparatus embodiment, the specification will not repeat the detailsgiven in the aforementioned method embodiment, but it should be clearthat the apparatus of this embodiment is capable of achieving everythingachieved in the aforementioned method embodiment.

An embodiment of this specification provides another server. When a useridentity verification request is received, first, a facial image and oneor more eye-print pair images corresponding to an identity verificationobject are received from a client. The number of the one or moreeye-print pair images corresponds to the number of eye-print collectionsteps. Then the facial image is compared to a preset facial image, andthe eye-print pair images are compared to preset eye-print templates.Successful identity verification information is sent to the client ifthe comparison results for the facial image and the eye-print pairimages meet preset conditions. Compared to the method of combiningfacial image recognition with live facial image verification commonlyused today when performing user identity verification, the embodimentsof this specification use multidimensional verification modes such asfacial image verification combined with eye-print image verification andlive eye-print image verification to perform user identity verification,thereby boosting the precision and reliability of the user identityverification method, and ensuring the security of apps used by the user.

Further, as an implementation of the method shown in FIG. 3, anembodiment of this specification provides a client, as shown in FIG. 7.The client may comprise: a collection unit 71 and sending unit 72.

The collection unit 71 is configured to collect a facial imagecorresponding to the identity verification object and one or moreeye-print pair images corresponding to the number of eye-printcollection steps.

The sending unit 72 is configured to send the facial image and theeye-print pair images to the server, causing the server to performidentity verification of the identity verification object.

It should be noted that this apparatus embodiment corresponds to theaforementioned method embodiment. For ease of reading, for thisapparatus embodiment, the specification will not repeat the detailsgiven in the aforementioned method embodiment, but it should be clearthat the apparatus of this embodiment is capable of achieving everythingachieved in the aforementioned method embodiment.

An embodiment of this specification provides a client which firstcollects a facial image and one or more eye-print pair imagescorresponding to an identity verification object, the number of the oneor more eye-print pair images corresponding to the number of eye-printcollection steps, then sends the facial image and the eye-print pairimages to the server, causing the server to perform identityverification of the identity verification object. Compared to the methodof combining facial image recognition with live facial imageverification, commonly used today when performing user identityverification, this embodiment uses multidimensional verification modessuch as facial verification combined with eye-print image verificationand live eye-print image verification to perform user identityverification, thereby boosting the precision and reliability of the useridentity verification method, and ensuring the security of apps used bythe user.

Further, as an implementation of the method shown in FIG. 4, anembodiment of this specification provides another client, as shown inFIG. 8. The client may comprise a collection unit 81, sending unit 82,receiving unit 83, and determination unit 84.

The collection unit 81 is configured to collect a facial image and oneor more eye-print pair images corresponding to an identity verificationobject, the number of the one or more eye-print pair imagescorresponding to the number of eye-print collection steps.

The sending unit 82 is configured to send the facial image and theeye-print pair images to the server, causing the server to performidentity verification of the identity verification object.

Further, the client also comprises a receiving unit 83.

The sending unit 82 is configured to send a user identity verificationrequest to a server.

The receiving unit 83 is configured to receive a facial quality scorethreshold and the number of eye-print collection steps corresponding tothe current mode and sent by the server.

The collection unit 81 is configured to obtain a facial imagecorresponding to the identity verification object based on the facialquality score threshold and to obtain one or more eye-print pair imagescorresponding to the number of eye-print collection steps.

Further, the client also comprises a determination unit 84.

The determination unit 84 is configured to determine whether the imagequality of the currently obtained facial image is greater than or equalto the facial quality score threshold; if so, the sending unit isconfigured to send the facial image to the server.

The determination unit 84 is also configured to determine whether theeye-print pair images meets preset eye-print liveness conditions.

The sending unit 81 is also configured to send the eye-print pair imagesto the server if conditions are met.

It should be noted that this apparatus embodiment corresponds to theaforementioned method embodiment. For ease of reading, this apparatusembodiment will not go over each detail given in the aforementionedmethod embodiment, but it should be clear that the apparatus of thisembodiment is capable of achieving everything achieved in theaforementioned method embodiment.

The specification provides another client. In one embodiment, the clientfirst collects a facial image and one or more eye-print pair imagescorresponding to an identity verification object, the number of the oneor more eye-print pair images corresponding to the number of eye-printcollection steps, then sends the facial image and the eye-print pairimages to the server, causing the server to perform identityverification of the identity verification object. Compared to the methodof combining facial image recognition with live facial imageverification, commonly used today when performing user identityverification, this embodiment uses multidimensional verification modessuch as facial verification combined with eye-print image verificationand live eye-print image verification to perform user identityverification, thereby boosting the precision and reliability of the useridentity verification method, and ensuring the security of apps used bythe user.

Further, as an implementation of the methods shown in FIG. 1 and FIG. 3,an embodiment of this specification provides a user identityverification system, as shown in FIG. 9. The user identity verificationsystem comprises a server 91 and a client 92.

The server 91 is configured to send a facial quality score threshold andthe number of eye-print collection steps corresponding to the currentmode to a client when a user identity verification request is received.

The client 92 is configured to obtain a facial image based on the facialquality score threshold and obtain one or more eye-print pair imagescorresponding to the number of eye-print collections steps.

The server 91 is also configured to receive a facial image sent by aclient and one or more eye-print pair images corresponding to the numberof eye-print collection steps; compare the facial image to a presetfacial image, and compare the eye-print pair images to preset eye-printtemplates; and send successful identity verification information to theclient if the comparison results for the facial image and the eye-printpair images meet preset conditions.

It should be noted that this apparatus embodiment corresponds to theaforementioned method embodiment. For ease of reading, for thisapparatus embodiment, the specification will not repeat the detailsgiven in the aforementioned method embodiment, but it should be clearthat the apparatus of this embodiment is capable of achieving everythingachieved in the aforementioned method embodiment.

In a user identity verification system provided by an embodiment of thisspecification, when a user identity verification request is received,first a facial image and one or more eye-print pair images correspondingto an identity verification object are received from a client. Thenumber of the one or more eye-print pair images corresponds to thenumber of eye-print collection steps. Then the facial image is comparedto a preset facial image, the eye-print pair images are compared topreset eye-print templates, and successful identity verificationinformation is sent to the client if the comparison results for thefacial image and the eye-print pair images meet preset conditions.Compared to the method of combining facial image recognition with livefacial image verification commonly used today when performing useridentity verification, this embodiment uses multidimensionalverification modes such as facial verification combined with eye-printimage verification and live eye-print image verification to perform useridentity verification, thereby boosting the precision and reliability ofthe user identity verification method, and ensuring the security of appsused by the user.

The user identity verification apparatus comprises a processor and amemory. The aforementioned virtual elements are all stored in the memoryas program units, and the processor executes these program units thatare stored in the memory to achieve corresponding functions.

The processor contains a kernel. The kernel retrieves the correspondingprogram units from the memory. There may be one or more kernels. Byadjusting kernel parameters, it is possible to solve the existingproblem of low precision in user identity verification methods.

The memory may include volatile memory on computer-readable media,random access memory (RAM), and/or non-volatile RAM, such as read-onlymemory (ROM) or flash RAM. The memory comprises at least one storagechip.

This application also provides a computer program product. When it isexecuted on a data processing device, it is suitable for executing andinitializing program code with the following method steps. As anexample,

a server is configured to send a facial quality score threshold and thenumber of eye-print collection steps corresponding to the current modeto a client when a user identity verification request is received;

a client is configured to obtain a facial image based on the facialquality score threshold and obtain one or more eye-print pair imagescorresponding to the number of eye-print collections steps; and

the server is also configured to receive a facial image sent by a clientand one or more eye-print pair images corresponding to the number ofeye-print collection steps; compare the facial image to a preset facialimage, and compare the eye-print pair images to preset eye-printtemplates; and send successful identity verification information to theclient if the comparison results for the facial image and the eye-printpair images meet preset conditions.

A person skilled in the art should understand that the embodiments ofthis application can be provided as methods, systems, or computerprogram products. Therefore, this application may employ a purelyhardware embodiment form, purely software embodiment form, or anembodiment form that combines software and hardware. Also, thisapplication may employ the form of computer program products achievedthrough one or more computer storage media (including but not limited tomagnetic disc memory, CD-ROM, and optical memory) comprisingcomputer-executable program code.

This application is described by referencing flow diagrams and/or blockdiagrams based on the user identity verification method, apparatus,system, and computer program product of this embodiment. It should beunderstood that computer program instructions can be used to achieveevery flow and/or block in the flow diagrams and/or block diagrams, aswell as combinations of flows and/or blocks in the flow diagrams and/orblock diagrams. These computer program instructions can be provided tothe processor of a general-purpose computer, special-purpose computer,embedded processing machine, or other programmable data processingdevice to produce a machine, causing the instructions executed by theprocessor of a computer or other programmable data processing device toproduce a device used to achieve the specified functions of one or moreflows in a flow diagram and/or one or more blocks in a block diagram.

These computer program instructions can also be stored incomputer-readable memory that can cause a computer or other programmabledata processing device to operate in a given mode, causing theinstructions stored in this computer-readable memory to generate aproduct comprising an instruction apparatus. This instruction apparatusachieves the functions specified in one or more flows of a flow chartand/or one or more blocks of a block diagram.

These computer program instructions can also be loaded onto a computeror other programmable data processing device, enabling the execution ofa series of operation steps on the computer or other programmable deviceto produce computer processing. Thus, the instructions executed on thecomputer or other programmable device provide steps for achieving thespecified functions of one or more flows in a flow chart and/or one ormore blocks in a block diagram.

In one typical configuration, the computation equipment comprises one ormore processors (CPUs), input/output interfaces, network interfaces, andinternal memory.

The memory could comprise the forms of volatile memory oncomputer-readable media, random access memory (RAM), and/or non-volatileRAM, such as read-only memory (ROM) or flash RAM. Memory is an exampleof computer-readable media.

Computer-readable media include permanent, nonpermanent, mobile, andimmobile media, which can achieve information storage through any methodor technology. The information may be computer-readable instructions,data structures, program modules, or other data. Examples of computerstorage media include, but are not limited to, Phase-change RAM (PRAM),Static RAM (SRAM), Dynamic RAM (DRAM), other types of Random AccessMemory (RAM), Read-Only Memory (ROM), Electrically Erasable ProgrammableRead-Only Memory (EEPROM), flash memory or other internal memorytechnologies, Compact Disk Read-Only Memory (CD-ROM), Digital VersatileDiscs (DVD) or other optical memories, cassettes, magnetic tape and diskmemories or other magnetic memory devices, or any other non-transmissionmedia, which can be used for storing information that can be accessed bya computation device. According to the definitions herein,computer-readable media exclude transitory computer-readable media(transitory media), such as modulated data signals and carriers.

The preceding are merely embodiments of this application. They are notused to limit this application. For persons skilled in the art, thisapplication could have various modifications and changes. All revisions,equivalent substitutions, and improvements made within the spirit andprinciples of this application shall fall within the scope of the claimsof this application.

What is claimed is:
 1. A non-transitory computer readable storage mediumconfigured with instructions executable by one or more processors tocause the one or more processors to perform operations comprising:receiving a facial quality score threshold and a number of eye-printcollection steps; obtaining a facial image of a user based on thereceived facial quality score threshold; obtaining one or more eye-printpair images of the user, a number of the obtained one or more eye-printpair images corresponding to the received number of eye-print collectionsteps; and sending the facial image and the one or more eye-print pairimages to the server to perform identity verification of the user. 2.The non-transitory computer readable storage medium of claim 1, whereinthe operations further comprise: before sending the facial image to theserver, determining that an image quality of the obtained facial imageis no less than the facial quality score threshold.
 3. Thenon-transitory computer readable storage medium of claim 1, wherein theoperations further comprise: before sending the one or more eye-printpair images to the server, determining that the one or more eye-printpair images meet preset eye-print liveness conditions.
 4. Thenon-transitory computer readable storage medium of claim 2, wherein theoperations further comprise: before sending the one or more eye-printpair images to the server, determining that the one or more eye-printpair images meet preset eye-print liveness conditions.
 5. Thenon-transitory computer readable storage medium of claim 1, wherein theoperations further comprise: before sending the facial image and the oneor more eye-print pair images to the server, performing preprocessing ofthe obtained facial image and one or more eye-print pair images, whereinsending the facial image and the one or more eye-print pair images tothe server comprises: sending the preprocessed facial image and thepreprocessed one or more eye-print pair images to the server.
 6. Thenon-transitory computer readable storage medium of claim 1, wherein theoperations further comprise: sending a user identity verificationrequest to the server, wherein the user identity verification requestcomprises identification information of the user to enable the server toperform the identity verification of the user.
 7. The non-transitorycomputer readable storage medium of claim 6, wherein the useridentification verification request is sent to the server when the userrequests performance of an account login or payment operation.
 8. Thenon-transitory computer readable storage medium of claim 1, wherein thereceived facial quality score threshold and the received number ofeye-print collection steps are sent by the server.
 9. The non-transitorycomputer readable storage medium of claim 8, wherein the received numberof eye-print collection steps correspond to a mode associated with anumber of eye-print templates corresponding to the user that are storedin a storage location.
 10. A non-transitory computer readable storagemedium configured with instructions executable by one or more processorsto cause the one or more processors to perform operations comprising:receiving a user identity verification request from a client; obtaininga number of eye-print templates corresponding to the user from a storagelocation, wherein the storage location is configured to store eye-printtemplates corresponding to different users; determining a current modeaccording to the number of obtained eye-print templates corresponding tothe user; and sending a facial quality score threshold and a number ofeye-print collection steps corresponding to the current mode to theclient to obtain a facial image of the user based on the facial qualityscore threshold and obtain one or more eye-print pair images of the usercorresponding to the number of eye-print collection steps.
 11. Thenon-transitory computer readable storage medium of claim 10, wherein theobtained number of eye-print templates corresponding to the user is noless than a preset threshold, wherein the determined current mode is anidentity verification mode, wherein the number of eye-print collectionsteps correspond to the identity verification mode.
 12. Thenon-transitory computer readable storage medium of claim 11, theoperations further comprising: receiving the facial image and the one ormore eye-print pair images corresponding to the user from the client,wherein the number of received one or more eye-print pair imagescorresponds to the number of eye-print collection steps; comparing thefacial image to a preset facial image, and comparing the one or moreeye-print pair images to eye-print templates corresponding to the user;and when comparison results for the facial image and the one or moreeye-print pair images meet preset conditions, sending successfulidentity verification information to the client.
 13. The non-transitorycomputer readable storage medium of claim 12, wherein: comparing thefacial image to the preset facial image comprises: using the facialimage and the preset facial image as input to a facial algorithm; andobtaining a facial comparison score corresponding to the user from thefacial algorithm.
 14. The non-transitory computer readable storagemedium of claim 12, wherein when the comparison results for the facialimage and the one or more eye-print pair images meet the presetconditions, updating the eye-print templates corresponding to the user.15. The non-transitory computer readable storage medium of claim 10,wherein the obtained number of eye-print templates corresponding to theuser is less than a preset threshold, wherein the determined currentmode is an eye-print enrollment mode, wherein and the number ofeye-print collection steps correspond to the eye-print enrollment mode.16. The non-transitory computer readable storage medium of claim 15, theoperations further comprising: receiving the one or more eye-print pairimages corresponding to the user from the client, wherein the number ofreceived one or more eye-print pair images corresponds to the number ofeye-print collection steps; and storing the received one or moreeye-print pair images in the storage location as eye-print templatescorresponding to the user.
 17. A method, comprising: receiving a useridentity verification request from a client; obtaining a number ofeye-print templates corresponding to the user from a storage location,wherein the storage location is configured to store eye-print templatescorresponding to different users; determining a current mode accordingto the number of obtained eye-print templates corresponding to the user;and sending a facial quality score threshold and a number of eye-printcollection steps corresponding to the current mode to the client toobtain a facial image of the user based on the facial quality scorethreshold and obtain one or more eye-print pair images of the usercorresponding to the number of eye-print collection steps.
 18. Themethod of claim 17, wherein the obtained number of eye-print templatescorresponding to the user is no less than a preset threshold, whereinthe determined current mode is an identity verification mode, whereinthe set facial quality score threshold and the number of eye-printcollection steps correspond to the identity verification mode.
 19. Themethod of claim 18, further comprising: receiving the facial image andthe one or more eye-print pair images corresponding to the user from theclient, wherein the number of received one or more eye-print pair imagescorresponds to the number of eye-print collection steps; comparing thefacial image to a preset facial image, and comparing the one or moreeye-print pair images to eye-print templates corresponding to the user;and when comparison results for the facial image and the one or moreeye-print pair images meet preset conditions, sending successfulidentity verification information to the client.
 20. The method of claim17, wherein the obtained number of eye-print templates corresponding tothe user is less than a preset threshold, wherein the determined currentmode is an eye-print enrollment mode, wherein the number of eye-printcollection steps correspond to the eye-print enrollment mode, the methodfurther comprising: receiving the one or more eye-print pair imagescorresponding to the user from the client, wherein the number ofreceived one or more eye-print pair images corresponds to the number ofeye-print collection steps; and storing the received one or moreeye-print pair images in the storage location as eye-print templatescorresponding to the user.